Spindle Detector A7

Module name: SpindleDetectorA7

Package: CEAMSModules 7.4.0

Version: 3.0.0

Overview

Class to detect spindles based on the a7 algorithm

Input	Format	Default	Description
`signals`	List of SignalModel	—	List of signal with dictionary of channels with SignalModel with properties : name: The name of the channel samples: The samples of the signal alias: The alias of the channel sample_rate: The sample rate of the signal start_time: The start time of the recording montage_index: The index of the montage used for this signal is_modified: Value caracterizing if the signal as been modify from the original
`thresholds`	dict	—	thresh_abs_sigma_pow_uv2 : threshold for the absolute sigma power (uv2) thresh_rel_sigma_pow_z : threshold for the relative sigma power (z-score) thresh_sigma_cov_z : threshold for the sigma covariance (z-score) thresh_sigma_cor_perc : threshold for the sigma correlation (%)
`event_group`	String	—	List of Event group to filter separated by comma (discard too long, short)
`event_name`	String	—	List of Event name to filter separated by comma (discard too long, short)
`artifact_events`	Pandas DataFrame (columns=[‘group’,’name’,’start_sec’,’duration_sec’,’channels’])	—	Selected events list for artifacts.
`frequency_band`	dict	—	frequency_band : Dictionary with the frequency band to use for the detection

Output	Format	Description
`events`	Pandas DataFrame (columns=[‘group’,’name’,’start_sec’,’duration_sec’,’channels’])	Events list for spindle detections.

Open Dev Tools -> New process in Snooz.
In the Module Library, find Spindle Detector A7 under the Detectors category.
Drag the module onto the process canvas.
Connect the required inputs from upstream modules (or set values in the Settings tab).
Connect outputs to downstream modules as needed.
Double-click the module to configure parameters in the Settings tab.
Run the process and inspect results in the Results tab.

Note

For general guidance on building processes with modules, see Explore examples.